Job Summary The Senior Data Scientist designs and deploys statistical, forecasting, and machine learning solutions to solve complex business problems. This role works with cross-functional teams to build production-ready models, generate actionable insights, and improve planning and decision-making at scale.

The role requires robust expertise in statistics, time series analysis, probabilistic forecasting, machine learning, and Google Cloud Platform (GCP).

Responsibilities

Statistical Modeling & Forecasting

Build and deploy statistical and probabilistic forecasting models for demand, capacity, and trend analysis

Apply time series methods including regression-based models, ARIMA/SARIMA, and state-space models

Define modeling assumptions, forecast uncertainty, and evaluation methods Machine Learning & Predictive Modeling

Build and deploy machine learning models for forecasting and prediction, including regression, tree-based models, gradient boosting and neural networks

Select statistical or ML approaches based on accuracy, interpretability, robustness, and operational needs

Develop features and run experiments to improve model performance MLOps & Production Deployment

Own the model lifecycle, including development, backtesting, deployment, monitoring, and retraining

Implement model monitoring, performance tracking, and data drift detection

Ensure models are versioned, reproducible, and production-ready Data Engineering & Modeling

Perform exploratory data analysis, feature engineering, and hypothesis testing on large, complex datasets





Identify data requirements for forecasting and predictive modeling, including key inputs, data gaps, and quality needs

Work with big data technologies and distributed data processing to support scalable modeling

Partner with data engineering teams to ensure data quality, availability, and efficient data pipelines Visualization & Insights

Create visualizations to communicate forecasts, trends, and model outputs

Translate model results into actionable insights for business and operational stakeholders Collaboration & Stakeholder Engagement

Work closely with product managers, engineers, and business teams to define forecasting and analytics requirements

Communicate modeling approaches, assumptions, and results clearly to technical and non-technical stakeholders Qualifications

4+ years of experience in data science, applied statistics, or machine learning

Strong foundation in statistics and experience applying statistical methods in production

Proven experience with time series analysis and probabilistic forecasting

Hands-on experience with machine learning models such as regression, boosting, and neural networks

Experience owning production data science models, including deployment and monitoring

Experience working with large datasets and using SQL and Python for analytical and modeling workflows

Proficiency in Python and common DS/ML libraries (e.g., pandas, NumPy, scikit-learn, statsmodels, PyTorch/TensorFlow)

Experience working on Google Cloud Platform (GCP)

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field

📌 Sr Data Scientist (Bengaluru)
🏢 Equinix
📍 Bengaluru